https://github.com/aaltoml/nsvqgs
공식 코드Compressing 3D Gaussian Splatting by Noise-Substituted Vector Quantization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Compressing 3D Gaussian Splatting by Noise-Substituted Vector Quantization
Next Best Sense: Guiding Vision and Touch with FisherRF for 3D Gaussian Splatting
Training-Free Hierarchical Scene Understanding for Gaussian Splatting with Superpoint Graphs
CoherentGS: Sparse Novel View Synthesis with Coherent 3D Gaussians
RI3D: Few-Shot Gaussian Splatting With Repair and Inpainting Diffusion Priors
GarmentDreamer: 3DGS Guided Garment Synthesis with Diverse Geometry and Texture Details
Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving
SplatAD: Real-Time Lidar and Camera Rendering with 3D Gaussian Splatting for Autonomous Driving
VRSplat: Fast and Robust Gaussian Splatting for Virtual Reality
Does 3D Gaussian Splatting Need Accurate Volumetric Rendering?
USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting
Empowering Vector Graphics with Consistently Arbitrary Viewing and View-dependent Visibility
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes
DEGSTalk: Decomposed Per-Embedding Gaussian Fields for Hair-Preserving Talking Face Synthesis
Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning
GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring
MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Survey
VPGS-SLAM: Voxel-based Progressive 3D Gaussian SLAM in Large-Scale Scenes
Compact 3D Scene Representation via Self-Organizing Gaussian Grids
Improving Adaptive Density Control for 3D Gaussian Splatting
GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond
SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.